






'''simple docstring'''





from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_UpperCamelCase						:						List[Any]  =					0

_UpperCamelCase						:						Optional[int]  =					[
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

_UpperCamelCase						:						Dict  =					[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

_UpperCamelCase						:						Union[str, Any]  =					tuple[int, int]


class  snake_case__      :




					def __init__(  self  :		Union[str, Any]				, _A  :		int				, _A  :		int				, _A  :		int				, _A  :		int				, _A  :		int				, _A  :		Node | None				, )    ->							None:
								UpperCAmelCase_      :       int          =       pos_x
								UpperCAmelCase_      :       List[str]          =       pos_y
								UpperCAmelCase_      :       List[Any]          =       (pos_y, pos_x)
								UpperCAmelCase_      :       Optional[int]          =       goal_x
								UpperCAmelCase_      :       Any          =       goal_y
								UpperCAmelCase_      :       Dict          =       g_cost
								UpperCAmelCase_      :       Any          =       parent
								UpperCAmelCase_      :       List[str]          =       self.calculate_heuristic()
								UpperCAmelCase_      :       Tuple          =       self.g_cost + self.h_cost




					def 		A      (  self  :		List[str]      )    ->							float:
								UpperCAmelCase_      :       Tuple          =       self.pos_x - self.goal_x
								UpperCAmelCase_      :       Optional[Any]          =       self.pos_y - self.goal_y
								if HEURISTIC == 1:
											return abs(_A      ) + abs(_A      )
								else:
											return sqrt(dy**2 + dx**2      )





					def __lt__(  self  :		Optional[Any]				, _A  :		Node      )    ->							bool:
								return self.f_cost < other.f_cost






class  snake_case__      :




					def __init__(  self  :		int				, _A  :		TPosition				, _A  :		TPosition      )    ->							int:
								UpperCAmelCase_      :       str          =       Node(start[1]				, start[0]				, goal[1]				, goal[0]				, 0				, _A      )
								UpperCAmelCase_      :       Dict          =       Node(goal[1]				, goal[0]				, goal[1]				, goal[0]				, 9_99_99				, _A      )

								UpperCAmelCase_      :       Tuple          =       [self.start]
								UpperCAmelCase_      :       list[Node]          =       []

								UpperCAmelCase_      :       List[Any]          =       False




					def 		A      (  self  :		int      )    ->							list[TPosition]:
								while self.open_nodes:
											# Open Nodes are sorted using __lt__
											self.open_nodes.sort()
											UpperCAmelCase_      :       List[Any]          =       self.open_nodes.pop(0      )

											if current_node.pos == self.target.pos:
														return self.retrace_path(_A      )

											self.closed_nodes.append(_A      )
											UpperCAmelCase_      :       Union[str, Any]          =       self.get_successors(_A      )

											for child_node in successors:
														if child_node in self.closed_nodes:
																	continue

														if child_node not in self.open_nodes:
																	self.open_nodes.append(_A      )
														else:
																	# retrieve the best current path
																	UpperCAmelCase_      :       int          =       self.open_nodes.pop(self.open_nodes.index(_A      )      )

																	if child_node.g_cost < better_node.g_cost:
																				self.open_nodes.append(_A      )
																	else:
																				self.open_nodes.append(_A      )

								return [self.start.pos]




					def 		A      (  self  :		Union[str, Any]				, _A  :		Node      )    ->							list[Node]:
								UpperCAmelCase_      :       int          =       []
								for action in delta:
											UpperCAmelCase_      :       List[str]          =       parent.pos_x + action[1]
											UpperCAmelCase_      :       Optional[int]          =       parent.pos_y + action[0]
											if not (0 <= pos_x <= len(grid[0]      ) - 1 and 0 <= pos_y <= len(_A      ) - 1):
														continue

											if grid[pos_y][pos_x] != 0:
														continue

											successors.append(
											    Node(
											        _A				, _A				, self.target.pos_y				, self.target.pos_x				, parent.g_cost + 1				, _A				, )      )
								return successors





					def 		A      (  self  :		Tuple				, _A  :		Node | None      )    ->							list[TPosition]:
								UpperCAmelCase_      :       Dict          =       node
								UpperCAmelCase_      :       str          =       []
								while current_node is not None:
											path.append((current_node.pos_y, current_node.pos_x)      )
											UpperCAmelCase_      :       Dict          =       current_node.parent
								path.reverse()
								return path






class  snake_case__      :




					def __init__(  self  :		int				, _A  :		TPosition				, _A  :		TPosition      )    ->							None:
								UpperCAmelCase_      :       List[str]          =       AStar(_A				, _A      )
								UpperCAmelCase_      :       Optional[Any]          =       AStar(_A				, _A      )
								UpperCAmelCase_      :       Union[str, Any]          =       False




					def 		A      (  self  :		str      )    ->							list[TPosition]:
								while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
											self.fwd_astar.open_nodes.sort()
											self.bwd_astar.open_nodes.sort()
											UpperCAmelCase_      :       int          =       self.fwd_astar.open_nodes.pop(0      )
											UpperCAmelCase_      :       Optional[int]          =       self.bwd_astar.open_nodes.pop(0      )

											if current_bwd_node.pos == current_fwd_node.pos:
														return self.retrace_bidirectional_path(
														    _A				, _A      )

											self.fwd_astar.closed_nodes.append(_A      )
											self.bwd_astar.closed_nodes.append(_A      )

											UpperCAmelCase_      :       Any          =       current_bwd_node
											UpperCAmelCase_      :       Union[str, Any]          =       current_fwd_node

											UpperCAmelCase_      :       Any          =       {
											    self.fwd_astar: self.fwd_astar.get_successors(_A      ),
											    self.bwd_astar: self.bwd_astar.get_successors(_A      ),
											}

											for astar in [self.fwd_astar, self.bwd_astar]:
														for child_node in successors[astar]:
																	if child_node in astar.closed_nodes:
																				continue

																	if child_node not in astar.open_nodes:
																				astar.open_nodes.append(_A      )
																	else:
																				# retrieve the best current path
																				UpperCAmelCase_      :       Any          =       astar.open_nodes.pop(
																				    astar.open_nodes.index(_A      )      )

																				if child_node.g_cost < better_node.g_cost:
																							astar.open_nodes.append(_A      )
																				else:
																							astar.open_nodes.append(_A      )

								return [self.fwd_astar.start.pos]





					def 		A      (  self  :		Any				, _A  :		Node				, _A  :		Node      )    ->							list[TPosition]:
								UpperCAmelCase_      :       int          =       self.fwd_astar.retrace_path(_A      )
								UpperCAmelCase_      :       str          =       self.bwd_astar.retrace_path(_A      )
								bwd_path.pop()
								bwd_path.reverse()
								UpperCAmelCase_      :       str          =       fwd_path + bwd_path
								return path


if __name__ == "__main__":
						# all coordinates are given in format [y,x]
						_UpperCamelCase						:						Tuple  =					(0, 0)
						_UpperCamelCase						:						List[Any]  =					(len(grid) - 1, len(grid[0]) - 1)
						for elem in grid:
												print(elem)

						_UpperCamelCase						:						str  =					time.time()
						_UpperCamelCase						:						str  =					AStar(init, goal)
						_UpperCamelCase						:						int  =					a_star.search()
						_UpperCamelCase						:						Dict  =					time.time() - start_time
						print(f'''AStar execution time = {end_time:f} seconds''')

						_UpperCamelCase						:						int  =					time.time()
						_UpperCamelCase						:						Any  =					BidirectionalAStar(init, goal)
						_UpperCamelCase						:						Optional[Any]  =					time.time() - bd_start_time
						print(f'''BidirectionalAStar execution time = {bd_end_time:f} seconds''')










'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available


_UpperCamelCase						:						Tuple  =					{
    'configuration_audio_spectrogram_transformer': [
        'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ASTConfig',
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase						:						Optional[int]  =					[
						    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'ASTForAudioClassification',
						    'ASTModel',
						    'ASTPreTrainedModel',
						]

try:
						if not is_speech_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase						:						int  =					['ASTFeatureExtractor']

if TYPE_CHECKING:
						from .configuration_audio_spectrogram_transformer import (
						    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    ASTConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_audio_spectrogram_transformer import (
												    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ASTForAudioClassification,
												    ASTModel,
												    ASTPreTrainedModel,
												)

						try:
												if not is_speech_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
						import sys

						_UpperCamelCase						:						List[str]  =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


